Pub Date : 2025-01-16DOI: 10.1109/TMAG.2025.3529855
Jiaxing Wang;Dazhi Wang;Sihan Wang;Wenhui Li
Physics-informed neural networks (PINNs) have significant potential for modeling and parameter design in engineering field. While most existing PINNs research focuses on fluid mechanics and thermodynamics, few studies explore its application in electromagnetic field modeling of electromagnetic devices. Modeling the permanent magnet eddy-current coupler (PMECC) to predict its performance characteristics based on geometric parameters and material properties is crucial for its design and optimization. An unsupervised modeling method for PMECC based on physics-informed radial basis neural networks (PIRBFNNs) is presented in this work. The modeling and solving of static magnetic field for devices excited by permanent magnets (PMs) is realized, which solves the problem of the traditional PINN fully connected structure with many parameters and difficult training. We use the magnetic vector potential as the solution objective without providing the magnetic field boundary parameters and without labeling data, which is an unsupervised learning paradigm. The magnetic field distribution and performance of the PMECC can be computed using only the structural parameters. The experimental results show that the proposed PIRBFNN method is basically consistent with the results of the finite element numerical method and the analytical method. Additionally, a transfer learning experimental study was conducted to validate the effectiveness of the network components and training methods proposed in this article. The proposed method can, furthermore, be applied to the modeling and analysis of various devices using PM excitations.
{"title":"Modeling of Permanent Magnet Eddy-Current Coupler Based on Unsupervised Physics-Informed Radial-Based Function Neural Networks","authors":"Jiaxing Wang;Dazhi Wang;Sihan Wang;Wenhui Li","doi":"10.1109/TMAG.2025.3529855","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3529855","url":null,"abstract":"Physics-informed neural networks (PINNs) have significant potential for modeling and parameter design in engineering field. While most existing PINNs research focuses on fluid mechanics and thermodynamics, few studies explore its application in electromagnetic field modeling of electromagnetic devices. Modeling the permanent magnet eddy-current coupler (PMECC) to predict its performance characteristics based on geometric parameters and material properties is crucial for its design and optimization. An unsupervised modeling method for PMECC based on physics-informed radial basis neural networks (PIRBFNNs) is presented in this work. The modeling and solving of static magnetic field for devices excited by permanent magnets (PMs) is realized, which solves the problem of the traditional PINN fully connected structure with many parameters and difficult training. We use the magnetic vector potential as the solution objective without providing the magnetic field boundary parameters and without labeling data, which is an unsupervised learning paradigm. The magnetic field distribution and performance of the PMECC can be computed using only the structural parameters. The experimental results show that the proposed PIRBFNN method is basically consistent with the results of the finite element numerical method and the analytical method. Additionally, a transfer learning experimental study was conducted to validate the effectiveness of the network components and training methods proposed in this article. The proposed method can, furthermore, be applied to the modeling and analysis of various devices using PM excitations.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-10"},"PeriodicalIF":2.1,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-14DOI: 10.1109/TMAG.2025.3529489
Mehdi Aliahmadi;Mojtaba Mirsalim;Jafar Milimonfared;Javad S. Moghani
This article presents the hybrid modeling of synchronous reluctance (SynRe) machines equipped with any number of Joukowsky flux barriers (JFBs). The rotor, which includes the JFBs, the flux guides (FGs), and tangential ribs, is modeled using the magnetic equivalent circuit (MEC) method, considering the iron nonlinearity. The reluctance of the JFBs and FGs is calculated through the conformal mapping (CM) and the Joukowsky function, and the reluctance network is used for other regions, e.g., tangential rib regions that are in deep saturation under normal operating conditions. The stator slots, slot openings, and the air gap are modeled using the Fourier-based (FB) method, i.e., sub-domain technique. The stator has double-layer distributed windings, and the stator iron is assumed to be infinitely permeable. The MEC and the FB models are directly coupled by applying the coupling boundary conditions (BCs) on the rotor’s outer surface. Then, the total system of equations is solved through an iterative process. As the proposed hybrid model (HM) can be applied to SynRe machines with any number of JFBs, the results, e.g., components of the magnetic flux density, electromagnetic torque, and back electromotive force (back EMF), are presented for two, four, and six JFBs per rotor pole. The finite-element method (FEM) validates the proposed hybrid analytical method.
{"title":"Hybrid Modeling of Joukowsky-Barrier Synchronous Reluctance Machines","authors":"Mehdi Aliahmadi;Mojtaba Mirsalim;Jafar Milimonfared;Javad S. Moghani","doi":"10.1109/TMAG.2025.3529489","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3529489","url":null,"abstract":"This article presents the hybrid modeling of synchronous reluctance (SynRe) machines equipped with any number of Joukowsky flux barriers (JFBs). The rotor, which includes the JFBs, the flux guides (FGs), and tangential ribs, is modeled using the magnetic equivalent circuit (MEC) method, considering the iron nonlinearity. The reluctance of the JFBs and FGs is calculated through the conformal mapping (CM) and the Joukowsky function, and the reluctance network is used for other regions, e.g., tangential rib regions that are in deep saturation under normal operating conditions. The stator slots, slot openings, and the air gap are modeled using the Fourier-based (FB) method, i.e., sub-domain technique. The stator has double-layer distributed windings, and the stator iron is assumed to be infinitely permeable. The MEC and the FB models are directly coupled by applying the coupling boundary conditions (BCs) on the rotor’s outer surface. Then, the total system of equations is solved through an iterative process. As the proposed hybrid model (HM) can be applied to SynRe machines with any number of JFBs, the results, e.g., components of the magnetic flux density, electromagnetic torque, and back electromotive force (back EMF), are presented for two, four, and six JFBs per rotor pole. The finite-element method (FEM) validates the proposed hybrid analytical method.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-23"},"PeriodicalIF":2.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-14DOI: 10.1109/TMAG.2025.3528776
{"title":"2024 Index IEEE Transactions on Magnetics Vol. 60","authors":"","doi":"10.1109/TMAG.2025.3528776","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3528776","url":null,"abstract":"","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"60 12","pages":"1-80"},"PeriodicalIF":2.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10841809","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-14DOI: 10.1109/TMAG.2025.3529742
Ezio Puppin;Maurizio Zani;Ermanno Pinotti
Magnetization reversals taking place in ferromagnetic materials can be detected using pickup coils wrapped around the sample, the so-called Barkhausen noise (BN). The voltage peaks induced in the coils depend both on the value ${Delta }M$ of each magnetization reversal and on the attenuation $V(x)$ of the inductive signal after traveling a distance x inside the material. Here, we present a procedure for obtaining $V(x)$ starting from the BN induced in two pickup coils separated by a distance variable between 2 and 40 mm. This procedure starts from the experimental values of R, the ratio of the signals induced in coincidence by the same magnetization reversal in the two coils, measured in a thin amorphous ribbon of Fe63B64Si8Ni15. Working with the signal ratio allows us to get rid of the dependency on ${Delta }M$ . A mathematical model for extracting $V(x)$ from the histogram of the measured values of R is presented.
{"title":"Attenuation of Magnetic Effects in Soft Amorphous Ribbons","authors":"Ezio Puppin;Maurizio Zani;Ermanno Pinotti","doi":"10.1109/TMAG.2025.3529742","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3529742","url":null,"abstract":"Magnetization reversals taking place in ferromagnetic materials can be detected using pickup coils wrapped around the sample, the so-called Barkhausen noise (BN). The voltage peaks induced in the coils depend both on the value <inline-formula> <tex-math>${Delta }M$ </tex-math></inline-formula> of each magnetization reversal and on the attenuation <inline-formula> <tex-math>$V(x)$ </tex-math></inline-formula> of the inductive signal after traveling a distance x inside the material. Here, we present a procedure for obtaining <inline-formula> <tex-math>$V(x)$ </tex-math></inline-formula> starting from the BN induced in two pickup coils separated by a distance variable between 2 and 40 mm. This procedure starts from the experimental values of R, the ratio of the signals induced in coincidence by the same magnetization reversal in the two coils, measured in a thin amorphous ribbon of Fe63B64Si8Ni15. Working with the signal ratio allows us to get rid of the dependency on <inline-formula> <tex-math>${Delta }M$ </tex-math></inline-formula>. A mathematical model for extracting <inline-formula> <tex-math>$V(x)$ </tex-math></inline-formula> from the histogram of the measured values of R is presented.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-6"},"PeriodicalIF":2.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-09DOI: 10.1109/TMAG.2025.3527486
Rui Zhang;Lei Shen
The neural network-based method for modeling magnetic materials enables the estimation of hysteresis B-H loop and core loss across a wide operation range. Transformers are neural networks widely used in sequence-to-sequence tasks. The classical Transformer modeling method suffers from high per-layer complexity and long recurrent inference time when dealing with long sequences. While down-sampling methods can mitigate these issues, they often sacrifice modeling accuracy. In this study, we propose MAG-Vision, which employs a vision Transformer (ViT) as the backbone for magnetic material modeling. It can shorten waveform sequences with minimal loss of information. We trained the network using the open-source magnetic core loss dataset MagNet. Experimental results demonstrate that MAG-Vision performs well in estimating hysteresis B-H loop and magnetic core losses. The average relative error of magnetic core losses for most materials is less than 2%. Experiments are designed to compare MAG-Vision with different network structures to validate its advantages in accuracy, training speed, and inference time.
{"title":"MAG-Vision: A Vision Transformer Backbone for Magnetic Material Modeling","authors":"Rui Zhang;Lei Shen","doi":"10.1109/TMAG.2025.3527486","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3527486","url":null,"abstract":"The neural network-based method for modeling magnetic materials enables the estimation of hysteresis B-H loop and core loss across a wide operation range. Transformers are neural networks widely used in sequence-to-sequence tasks. The classical Transformer modeling method suffers from high per-layer complexity and long recurrent inference time when dealing with long sequences. While down-sampling methods can mitigate these issues, they often sacrifice modeling accuracy. In this study, we propose MAG-Vision, which employs a vision Transformer (ViT) as the backbone for magnetic material modeling. It can shorten waveform sequences with minimal loss of information. We trained the network using the open-source magnetic core loss dataset MagNet. Experimental results demonstrate that MAG-Vision performs well in estimating hysteresis B-H loop and magnetic core losses. The average relative error of magnetic core losses for most materials is less than 2%. Experiments are designed to compare MAG-Vision with different network structures to validate its advantages in accuracy, training speed, and inference time.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-6"},"PeriodicalIF":2.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-08DOI: 10.1109/TMAG.2025.3526872
Petru Andrei;Nicholas Carlstedt
High-gradient magnetic chromatography (HGMC) is a technique for selectively separating magnetic particles (MPs) according to their magnetic susceptibilities. We develop a mathematical model for HGMC that includes the effects of magnetic force, Brownian motion, gravity, and viscous drag. We then use this model to interpret recently reported experimental results and to distinguish these efforts from other work on high-gradient magnetic separation (HGMS) in the literature. Special emphasis is given to analyzing the main limitations of HGMC with regards to particle size and magnetic susceptibility. Our simulations show that HGMC can separate paramagnetic particles with magnetic susceptibilities as low as $10^{-4}$ to $10^{-3}$ and diameters down to a few tens of nanometers. Finally, we propose and discuss various alternative HGMC designs.
{"title":"Simulation Study of High-Gradient Magnetic Chromatography","authors":"Petru Andrei;Nicholas Carlstedt","doi":"10.1109/TMAG.2025.3526872","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3526872","url":null,"abstract":"High-gradient magnetic chromatography (HGMC) is a technique for selectively separating magnetic particles (MPs) according to their magnetic susceptibilities. We develop a mathematical model for HGMC that includes the effects of magnetic force, Brownian motion, gravity, and viscous drag. We then use this model to interpret recently reported experimental results and to distinguish these efforts from other work on high-gradient magnetic separation (HGMS) in the literature. Special emphasis is given to analyzing the main limitations of HGMC with regards to particle size and magnetic susceptibility. Our simulations show that HGMC can separate paramagnetic particles with magnetic susceptibilities as low as <inline-formula> <tex-math>$10^{-4}$ </tex-math></inline-formula> to <inline-formula> <tex-math>$10^{-3}$ </tex-math></inline-formula> and diameters down to a few tens of nanometers. Finally, we propose and discuss various alternative HGMC designs.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 2","pages":"1-10"},"PeriodicalIF":2.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10833827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-08DOI: 10.1109/TMAG.2025.3527341
Allison Harpel;Md Toaha Anas;Alex Wege;Rhonda R. Franklin;Bethanie J. H. Stadler
Magnetic nanowires (MNWs) have been proposed for use in numerous applications due to their tunability and scale, but due to the same tunability that makes MNWs so versatile, tight quality control is needed to make the transition from research labs to industry. Currently, template-assisted electrodeposition is a promising fabrication method, but there is no quick, low-cost method to effectively quantify the fill factor (FF) of the templated wires. Here, we evaluate the efficacy of a copper seed layer to fabricate cobalt MNWs using quantitative ferromagnetic resonance (FMR). The deposition quality is assessed by FF and saturation magnetization (MS). First, the quality is evaluated by common, qualitative, or semiquantitative methods, which are then compared to the quantitative values measured from FMR. The copper seed layer is demonstrated to improve FF while maintaining MNW quality. For the seeded sample, FMR measured FF at 12.3% $pm ~0.4$ %, with an MNW MS of $1.64~pm ~0.10$ T. For the sample without a seed, FMR measured FF at 9.0% $pm ~0.4$ % with an MNW MS of $1.62~pm ~0.13$ T. These quantitative measurements were corroborated by all the qualitative and semiquantitative results, indicating that nondestructive FMR is a viable method to quantify FF and quickly evaluate the quality of templated MNWs.
{"title":"Nondestructive Ferromagnetic Resonance Measurements Validate the Efficacy of a Seed Layer in Cobalt Magnetic Nanowire Fabrication","authors":"Allison Harpel;Md Toaha Anas;Alex Wege;Rhonda R. Franklin;Bethanie J. H. Stadler","doi":"10.1109/TMAG.2025.3527341","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3527341","url":null,"abstract":"Magnetic nanowires (MNWs) have been proposed for use in numerous applications due to their tunability and scale, but due to the same tunability that makes MNWs so versatile, tight quality control is needed to make the transition from research labs to industry. Currently, template-assisted electrodeposition is a promising fabrication method, but there is no quick, low-cost method to effectively quantify the fill factor (FF) of the templated wires. Here, we evaluate the efficacy of a copper seed layer to fabricate cobalt MNWs using quantitative ferromagnetic resonance (FMR). The deposition quality is assessed by FF and saturation magnetization (MS). First, the quality is evaluated by common, qualitative, or semiquantitative methods, which are then compared to the quantitative values measured from FMR. The copper seed layer is demonstrated to improve FF while maintaining MNW quality. For the seeded sample, FMR measured FF at 12.3% <inline-formula> <tex-math>$pm ~0.4$ </tex-math></inline-formula>%, with an MNW MS of <inline-formula> <tex-math>$1.64~pm ~0.10$ </tex-math></inline-formula> T. For the sample without a seed, FMR measured FF at 9.0% <inline-formula> <tex-math>$pm ~0.4$ </tex-math></inline-formula>% with an MNW MS of <inline-formula> <tex-math>$1.62~pm ~0.13$ </tex-math></inline-formula> T. These quantitative measurements were corroborated by all the qualitative and semiquantitative results, indicating that nondestructive FMR is a viable method to quantify FF and quickly evaluate the quality of templated MNWs.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-9"},"PeriodicalIF":2.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10833744","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hot-deformed (HD) Nd-Fe-B magnet exhibits good magnetic and mechanical properties, which are dictated by the thermomechanical behavior of the feedstock during the hot deformation process. To enhance the HD magnet properties, the hot deformation behavior of the Nd-Fe-B material must be well understood and an accurate model of the process must be established and validated. In this work, the hot deformation behaviors of the Nd-Fe-B magnet were studied by experiments and simulations. Experiments were conducted using a thermomechanical simulator at temperatures ranging from 740 °C to 820 °C and the strain rates between 0.001 and 0.05 s−1. Results indicated that the flow stress was significantly affected by strain, temperature, and strain rate. Therefore, a modified constitutive model was developed to incorporate the effects of these three factors. The model achieved a correlation coefficient of 0.991, and further was implemented for the simulation of the forming processes. The simulated results matched the experimental ones very well. Furthermore, microstructural analysis and magnetic properties results showed the microstructure and magnetic properties were sensitive to temperature and strain rate, similar to the effective strain. Finally, the modified model was used to simulate the backward-extruded (BE) process for magnetic rings with high precision, verifying the applicability of the modified constitutive model. The method combining experiments, simulation, and microstructural analysis provides an efficient tool for obtaining high-performance HD magnets and designing process routes in engineering.
{"title":"Modeling of Hot Deformation Behavior of the Nd-Fe-B Permanent Magnet and Its Application in Forming of Magnetic Ring","authors":"Junyou Yang;Jun Li;Shaoxun Liu;Tao Liu;Lei Zhou;Xinghua Cheng;Xiaodong Li;Shuzhou Yu;Ying Chang;Xiaojun Yu;Bo Li","doi":"10.1109/TMAG.2025.3527030","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3527030","url":null,"abstract":"Hot-deformed (HD) Nd-Fe-B magnet exhibits good magnetic and mechanical properties, which are dictated by the thermomechanical behavior of the feedstock during the hot deformation process. To enhance the HD magnet properties, the hot deformation behavior of the Nd-Fe-B material must be well understood and an accurate model of the process must be established and validated. In this work, the hot deformation behaviors of the Nd-Fe-B magnet were studied by experiments and simulations. Experiments were conducted using a thermomechanical simulator at temperatures ranging from 740 °C to 820 °C and the strain rates between 0.001 and 0.05 s−1. Results indicated that the flow stress was significantly affected by strain, temperature, and strain rate. Therefore, a modified constitutive model was developed to incorporate the effects of these three factors. The model achieved a correlation coefficient of 0.991, and further was implemented for the simulation of the forming processes. The simulated results matched the experimental ones very well. Furthermore, microstructural analysis and magnetic properties results showed the microstructure and magnetic properties were sensitive to temperature and strain rate, similar to the effective strain. Finally, the modified model was used to simulate the backward-extruded (BE) process for magnetic rings with high precision, verifying the applicability of the modified constitutive model. The method combining experiments, simulation, and microstructural analysis provides an efficient tool for obtaining high-performance HD magnets and designing process routes in engineering.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-13"},"PeriodicalIF":2.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-31DOI: 10.1109/TMAG.2024.3524600
Xuyang Yu;Enshuo Liu;Chunguang Fan;Bo Zhao;Jiubin Tan
Based on the prototype Halbach planar magnet array (HPMA), a honeycomb Halbach flexible permanent magnet array (HHFA) is proposed in this article. HHFA can effectively optimize the magnetic field distribution, increase the magnetic field strength, and reduce the magnetic field distortion. The magnetic flux density distribution for HHFA was obtained through a numerical analytical approach. The simulation and comparative analysis show that the intensity amplitude of the magnetic field generated by HHFA is 23% higher than that of HPMA, and the periodic distortion rate, amplitude fluctuation of the magnetic field, and harmonic distortion of HHFA are optimized compared with HPMA. The simulation results demonstrate that magnetically levitated planar motor (MLPM) employing HHFA exhibits superior electromagnetic thrust coefficient and electromagnetic force stability compared to MLPM utilizing HPMA.
{"title":"Honeycomb Halbach Flexible Permanent Magnet Array for Magnetically Levitated Planar Motor","authors":"Xuyang Yu;Enshuo Liu;Chunguang Fan;Bo Zhao;Jiubin Tan","doi":"10.1109/TMAG.2024.3524600","DOIUrl":"https://doi.org/10.1109/TMAG.2024.3524600","url":null,"abstract":"Based on the prototype Halbach planar magnet array (HPMA), a honeycomb Halbach flexible permanent magnet array (HHFA) is proposed in this article. HHFA can effectively optimize the magnetic field distribution, increase the magnetic field strength, and reduce the magnetic field distortion. The magnetic flux density distribution for HHFA was obtained through a numerical analytical approach. The simulation and comparative analysis show that the intensity amplitude of the magnetic field generated by HHFA is 23% higher than that of HPMA, and the periodic distortion rate, amplitude fluctuation of the magnetic field, and harmonic distortion of HHFA are optimized compared with HPMA. The simulation results demonstrate that magnetically levitated planar motor (MLPM) employing HHFA exhibits superior electromagnetic thrust coefficient and electromagnetic force stability compared to MLPM utilizing HPMA.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 2","pages":"1-9"},"PeriodicalIF":2.1,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-31DOI: 10.1109/TMAG.2024.3524638
Xian Li;Xiuhe Wang;Wenliang Zhao
Aiming at the common faults of demagnetization and rotor eccentricity (RE) in permanent magnet (PM) synchronous motor, the electromagnetic field analysis under the faults and a nonintrusive fault diagnosis and localization technique are investigated in this article. Initially, a PM segmentation model is developed, and a general solution is derived for surface-mounted PM motor with local irreversible demagnetization fault (LIDF) accounting for core saturation, which can precisely simulate LIDF in arbitrary regions. Additionally, an equivalent transformation method is introduced to emulate the nonuniform magnetic field arising from RE. The validity and correctness of the proposed models are confirmed by finite element analysis and experiments. Furthermore, the effects caused by the faults on the no-load electromagnetic performance are analyzed, based on which a diagnosis technique for rotor faults using coil BEMF (CBEMF) is proposed. The localization of the LIDF is achieved by integration with the least square method, and the eccentric angle and ratio are determined by combining with a deep neural network (DNN). Overall, the proposed model can provide an important reference for rotor failure risk assessment, fault-tolerant optimization, and maintenance strategy.
{"title":"Electromagnetic Field Analysis and Diagnosis of Rotor Demagnetization and Eccentricity Faults in SPMSM","authors":"Xian Li;Xiuhe Wang;Wenliang Zhao","doi":"10.1109/TMAG.2024.3524638","DOIUrl":"https://doi.org/10.1109/TMAG.2024.3524638","url":null,"abstract":"Aiming at the common faults of demagnetization and rotor eccentricity (RE) in permanent magnet (PM) synchronous motor, the electromagnetic field analysis under the faults and a nonintrusive fault diagnosis and localization technique are investigated in this article. Initially, a PM segmentation model is developed, and a general solution is derived for surface-mounted PM motor with local irreversible demagnetization fault (LIDF) accounting for core saturation, which can precisely simulate LIDF in arbitrary regions. Additionally, an equivalent transformation method is introduced to emulate the nonuniform magnetic field arising from RE. The validity and correctness of the proposed models are confirmed by finite element analysis and experiments. Furthermore, the effects caused by the faults on the no-load electromagnetic performance are analyzed, based on which a diagnosis technique for rotor faults using coil BEMF (CBEMF) is proposed. The localization of the LIDF is achieved by integration with the least square method, and the eccentric angle and ratio are determined by combining with a deep neural network (DNN). Overall, the proposed model can provide an important reference for rotor failure risk assessment, fault-tolerant optimization, and maintenance strategy.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 3","pages":"1-13"},"PeriodicalIF":2.1,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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